Results 51 to 60 of about 1,984 (174)

Unraveling the Spatiotemporal Dynamics and Nonlinear Drivers of Green Transition of Farmland Use in Major Grain‐Producing Areas: A Case Study of Jiangsu Province, China

Land Degradation &Development, EarlyView.
ABSTRACT Promoting the green transition of farmland use (GTFU) in major grain‐producing areas is essential for ensuring food security and advancing sustainable agricultural development. However, existing studies on GTFU have predominantly relied on static cross‐sectional analyses, with insufficient attention paid to its nonlinear driving mechanisms. To
Zhixian Sun, Yixuan Lu, Xinyue Zheng, Dongmei Zhang, Yian Xu, Guanxin Yao   +5 more
wiley   +1 more source

The Use of Hyperparameter Tuning in Model Classification: A Scientific Work Area Identification

JOIV: International Journal on Informatics Visualization
This research aims to investigate the effectiveness of hyperparameter tuning, particularly using Optuna, in enhancing the classification performance of machine learning models on scientific work reviews. The study focuses on automating the classification
Nadya Alinda Rahmi, Sarjon Defit, - Okfalisa   +2 more
doaj   +1 more source

BayesianKAN: A reaction condition optimization framework integrating Kolmogorov‐Arnold network and Bayesian optimization

Smart Molecules, EarlyView.
A novel BayesianKAN framework integrates Kolmogorov‐Arnold networks with Bayesian optimization to efficiently navigate complex factor spaces, accelerating the discovery of optimal reaction conditions for chemical synthesis. Abstract Efficient optimization of chemical reaction conditions is crucial for enhancing reaction yield and selectivity, yet ...
Juntao Wang, Yujing Zhao, Peiyu Yi, Liyuan Duan, Qingwei Meng, Qilei Liu   +5 more
wiley   +1 more source

Forecasting grocery item sales using gradient boosting models: A study of GridSearchCV, RandomizedSearchCV, and optuna optimization approaches

Ain Shams Engineering Journal
This study introduces predictive modeling based on Extreme Gradient Boosting (XGBoost), which utilizes Optuna for hyperparameter optimization and evaluates performance against GridSearchCV and RandomizedSearchCV using a 500-day dataset.
Puja Supakar, Mitali Sarkar, Biswajit Sarkar   +2 more
doaj   +1 more source

A Context‐Aware Decision Support Framework for Scientific Experiment Configuration

Software: Practice and Experience, EarlyView.
ABSTRACT Introduction Defining an experimental configuration is a complex decision problem for early‐stage researchers, who must map goals, constraints, and requirements onto datasets, algorithms, and parameter settings that directly affect experimental outcomes.
Pouriya Miri, Vlado Stankovski, Kristina Veljković, Petar Kochovski   +3 more
wiley   +1 more source

Temperature Prediction of Wet Clutch Friction Pair Based on Optuna-LSTM Neural Network

Applied Sciences
As critical actuating components in vehicular transmission systems, wet clutches exhibit strongly nonlinear thermal responses in their friction pairs during engagement operations.
Yuqi Yang, Chengyun Su, Zhifei Wang, Chao Zhou, Aolong Zhang   +4 more
doaj   +1 more source

Decreasing the Environmental Impact of the Electric Steelmaking Route Through Advanced Modelling Techniques

steel research international, EarlyView.
Ensemble models are adopted to estimate the sterile content of scraps arriving to the scrap yard. Feed‐forward neural networks are exploited to estimate steel composition and temperature after Ladle furnace. The models are validated on data from two steelworks very satisfactory results and are inherently transferable to other steelworks, as they are ...
Valentina Colla, Antonella Zaccara, Stefano Dettori, Laura Laid, Ismael Matino, Silvia Cateni, Teresa Annunziata Branca, Lorenzo Vannini   +7 more
wiley   +1 more source

Fine‐tuning ab initio XANES spectra calculations using the Bayesian optimization algorithm

Journal of Synchrotron Radiation, EarlyView.
A Bayesian optimization technique is used to tune the FEFF and FDMNES packages and to improve matching between theoretical and experimental spectra. The tests were performed on monometallic Ni, Fe and Pd K‐edge XANES spectra using several different spectrum similarity metrics.Theoretical modeling of X‐ray absorption near‐edge structure (XANES) spectra ...
Andrey A. Sapronov, Dmitry E. Doronkin, Jan-Dierk Grunwaldt   +2 more
wiley   +1 more source

Development and Clinical Utility of Machine Learning Models for Prediction of Same‐Day Discharge in Outpatient Hip and Knee Replacement: A Prognostic Study

Acta Anaesthesiologica Scandinavica, Volume 70, Issue 8, September 2026.
ABSTRACT Background Hip and knee replacement are common procedures with an increasing focus on same‐day surgery. However, capacity constraints limit the number of eligible patients actually being scheduled for same‐day discharge, calling for further selection of those with the highest likelihood of same‐day discharge.
Christoffer C. Jørgensen, Jakob B. Frederiksen, Henrik Kehlet, Martin Lindberg‐Larsen, Kirill Gromov, Claus Varnum, Thomas Jakobsen, Manuel Josef Bieder, Mikkel Rathsach Andersen, Søren Overgaard, Torben B. Hansen, Troels Petersen   +11 more
wiley   +1 more source

MSPCIFormer: A Multi‐Scale Patching Channel‐Independent Transformer for Cryptocurrency Price Forecasting

Expert Systems, Volume 43, Issue 9, September 2026.
ABSTRACT Forecasting cryptocurrency prices remains challenging due to extreme volatility, regime‐dependent dynamics, and unstable cross‐asset correlations. Statistical methods such as ARIMA and GARCH assume stationarity and linear dependence structures, making them inadequate for capturing non‐linear temporal patterns in high volatile cryptocurrency ...
Huali Zhao, Martin Crane, Marija Bezbradica   +2 more
wiley   +1 more source